187 citations · 477 across the 24 of their papers we have counts for
9 papers · 1 filter
Large Language Model Sourcing: A Survey
Liang Pang, Jia Gu, Sunhao Dai +7
Due to the black-box nature of large language models (LLMs) and the realism of their generated content, issues such as hallucinations, bias, unfairness, and copyright infringement…
KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation
Changle Qu, Sunhao Dai, Ke Guo +7
Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interactions, and highly engaging user experien…
Revisiting Clustering of Neural Bandits: Selective Reinitialization for Mitigating Loss of Plasticity
Zhiyuan Su, Sunhao Dai, Xiao Zhang
Clustering of Bandits (CB) methods enhance sequential decision-making by grouping bandits into clusters based on similarity and incorporating cluster-level contextual information,…
GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents
Yuqi Zhou, Sunhao Dai, Shuai Wang +3
Recent Graphical User Interface (GUI) agents replicate the R1-Zero paradigm, coupling online Reinforcement Learning (RL) with explicit chain-of-thought reasoning prior to object gr…
NExT-Search: Rebuilding User Feedback Ecosystem for Generative AI Search
Sunhao Dai, Wenjie Wang, Liang Pang +4
Generative AI search is reshaping information retrieval by offering end-to-end answers to complex queries, reducing users' reliance on manually browsing and summarizing multiple we…
Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
Haoyu Wang, Sunhao Dai, Haiyuan Zhao +6
Previous studies have found that PLM-based retrieval models exhibit a preference for LLM-generated content, assigning higher relevance scores to these documents even when their sem…
CHOP: Mobile Operating Assistant with Constrained High-frequency Optimized Subtask Planning
Yuqi Zhou, Shuai Wang, Sunhao Dai +4
The advancement of visual language models (VLMs) has enhanced mobile device operations, allowing simulated human-like actions to address user requirements. Current VLM-based mobile…
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
Jiakai Tang, Sunhao Dai, Teng Shi +5
Sequential Recommendation (SeqRec) aims to predict the next item by capturing sequential patterns from users' historical interactions, playing a crucial role in many real-world rec…
Few-shot LLM Synthetic Data with Distribution Matching
Jiyuan Ren, Zhaocheng Du, Zhihao Wen +4
As large language models (LLMs) advance, their ability to perform in-context learning and few-shot language generation has improved significantly. This has spurred using LLMs to pr…